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# Senior Data Engineer

- **Company:** TRINZIC CORP
- **Location:** Beavercreek, OH, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Airflow, Apache HTTP Server, Big Data, Code Review, Data Architecture, Information Engineering, Data Infrastructure, Data Integration, Extract Transform Load (ETL), Data Transformation, Data Systems, Web Development, Distributed Computing Environment, Distributed Systems, Django Web Framework, Fault Tolerance, Python (Programming Language), PostgreSQL, Power BI, Standard Sql, Software Engineering, SQL Databases, Tableau (Software), Web Applications, Workflow Management Systems, Data Logging, Data Processing, Apache Spark, Parallel Computation, Backend, Git, Microsoft Fabric, Pytest, Data Lakes, Kubernetes, Dask, Celery, Software Version Control, Data Pipelines, Docker, Databricks
- **Published:** October 9, 2026
- **Apply:** https://dejobs.org/x/x/BD238884BFAE4E0D8C690AEF47E03756/job/

## About the Role

Required:

 * Bachelor's degree in a technical discipline.
 * 7+ years of experience in data engineering, software engineering, data platform engineering, or related fields.
 * 5+ years of direct Python development experience, including Django web application development.
 * Strong SQL and data modeling experience, including normalization, star schemas, and related modeling techniques.
 * Experience with large-scale analytical table formats such as Apache Iceberg, Delta Lake, or similar solutions.
 * Experience developing production-quality software and data solutions, including testing, documentation, monitoring, and maintainability.
 * Experience designing and implementing robust ETL pipelines, including distributed and parallel processing, workflow orchestration, fault tolerance, error handling, and idempotent processing.
 * Proficiency with Git and modern version control practices, including branching, merging, code review, and collaborative development workflows.
 * Experience with Power BI or Tableau
 * Demonstrated ability to work independently and provide sound technical recommendations.
 * Strong communication and stakeholder engagement skills.
 * The ability to obtain a Secret Security Clearance.

Desired:

 * Experience with dbt, Databricks, or similar technologies.
 * Experience with workflow orchestration and task-processing technologies such as Airflow, Dagster, or Celery.
 * Experience with distributed processing frameworks such as Spark, Dask, or Ray.
 * Experience processing and optimizing datasets exceeding 100GB.
 * Experience solving performance, scalability, and resource-constrained data engineering challenges.
 * Experience developing, deploying, and operating containerized applications using technologies such as Docker and Kubernetes in cloud and on-premises environments.
 * Experience serving as a technical lead or solution architect.
 * Python
 * Django / Django REST Framework
 * SQL / PostgreSQL
 * dbt
 * Apache Iceberg
 * Microsoft Fabric or Databricks
 * Spark, Dask, or Ray
 * Dagster, Airflow, or Celery
 * Docker / Kubernetes
 * Active Secret clearance

Ready to Make a Difference?

## Description

KBR is seeking a Senior Data Engineer (Lakehouse & Application Development) to design, develop, and optimize modern data platforms and web-based applications supporting Department of Defense Science & Engineering (S&E) initiatives.

This role combines backend web development and data engineering to design, build, and sustain an on-premises data platform supporting Science & Engineering (S&E) data integration, management, and analysis.

The ideal candidate is a proactive technical leader who can independently evaluate requirements, develop backend and data-processing solutions, and solve complex engineering challenges involving large datasets, distributed systems, incremental updates, and constrained resources., * Design, develop, and maintain web-based applications and APIs using Python and Django.

 * Collaborate with stakeholders to translate mission needs into scalable technical solutions.
 * Develop ETL/ELT pipelines with strong testing, logging, and exception-handling practices (pytest).
 * Design memory-efficient Python solutions using streaming, generators, incremental processing, and resource-conscious techniques.
 * Build and optimize dbt models, data transformation workflows, and Lakehouse data-processing pipelines.
 * Design and maintain scalable Lakehouse architecture supporting S&E data integration, governance, and analysis.
 * Develop Python-based data processing solutions for tabular, text, image, video, and geospatial datasets.
 * Evaluate technical alternatives and recommend architectures, technologies, and implementation approaches.
 * Design and optimize Apache Iceberg tables using effective partitioning, data layout, and maintenance strategies to support efficient querying and large-scale data processing.